Scientific Article

On the improvement of accommodation to non-individual HRTFs via VR active learning and inclusion of a 3D room response

Sorbonne Université, CNRS, UMR 7190, Institut Jean Le Rond ∂’Alembert, 75252 Paris, France

^* Corresponding author: david.poirier-quinot@sorbonne-universite.fr

Received: 7 November 2020
Accepted: 14 May 2021

Abstract

This study examines the efficiency of a training protocol using a virtual reality application designed to accelerate individual’s selection of, and accommodation to, non-individualized HRTF profiles. This training introduces three elements to hasten audio localization performance improvement: an interactive HRTF selection method, a parametric training program based on active learning, and a relatively dry room acoustic simulation designed to increase the quantity of spatial cues presented. Participants rapidly selected an HRTF (≈5 min) followed by training over three sessions of 12 min distributed over 5 days. To study the impact of the room acoustic component on localization performance evolution, participants were divided into two groups: one acting as control reference, training with only anechoic renderings, the other training in reverberant conditions. The efficiency of the training program was assessed across groups and the entire protocol was assessed through direct comparisons with results reported in previous studies. Results indicate that the proposed training program led to improved learning rates compared to that of previous studies, and that the included room response accelerated the learning process.